1. Field of the Invention
The present invention relates to a digital signal error reduction apparatus which is capable of reducing static quickly and changing interferences quickly through the transmission of digital signals, thereby increasing the accuracy of symbol detection.
2. Description of Prior Arts
The major impairments of any transmission scheme are nonlinear distortions, multipath distortions, co-channel interference, and time changing variants thereof.
In analog systems, these impairments are typically compensated through the use of a "Ghost Canceling Tuner" or an adaptive equalizer. For this purpose, the Broadcasting Technology Association (BTA) in Japan developed a training reference signal which is to be inserted into an NTSC (National Television System Committee) television transmission for use by an equalizer. In the equalizer, the received training signal is compared with a stored reference signal. Any difference of data between the received training signal and the stored reference signal may be used to compute a solution for filter tap-coefficient values which are used to compensate for errors. This is a practical application for the NTSC television transmission system due to previously unused, and thus available, time intervals in a data format into which the stored reference signal could be easily, though costly, inserted.
In digital systems, these impairments are typically compensated through the use of a decision feedback adaptive equalizer. Unlike the analog NTSC transmission scheme, digital transmission schemes generally do not contain empty or available time intervals into which a training reference signal may be inserted. A data stream is comprised of a fixed number of coded digital symbol data in a continuous and, for example in 32 QAM, a spectrum-balanced and random-like sequence. However, since the symbol data of a digital system is restricted to a small number of discrete values, a decision device may be used to determine the best choice value for each symbol. A training signal may be computed by passing a recovered digital signal through such a decision device. If the error is sufficiently small, the decision device will almost always select the correct value for each symbol in the signal. A subtraction of an input of the decision device from the computed training signal results in the error signal. This error signal can be used to compute tap-coefficients for a filter and to compensate for errors in the same manner as the analog system. This system has been utilized successfully in controlled environments such as cable based modem systems in which general characteristics of the signal path are known and impairments rarely rise above expected levels. For terrestrial broadcast systems, it imposes strict limitations such that when a distortion level rises to a height at which the decision device can no longer select the correct symbol for a given input, its output can no longer be used as the training reference signal. Therefore, the computed reference signal is incorrect. Thus, the derived error data is also erroneous and results in incorrect tap-coefficient computation. Derivation of an error signal which can be used for tap-coefficient computation under this condition, in the absence of a training signal, is referred to as blind equalization.
One example of a blind equalization algorithm was developed by Giorgio Picchi and Giancarlo Prati and is referred to as the "Stop-and-Go" algorithm (see "Blind Equalization and Carrier Recovery Using a "Stop and Go" Decision-Directed Algorithm" by Picchi and Prati, IEEE Transactions on Communications, Vol. COM-35, No. 9, September 1987). Picchi and Prati introduced a binary switching algorithm which inhibits a coefficient update from any unreliable data point in the error signal. Simply put, the algorithm `stops` when a data point from a standard error signal fails a reliability check, and `goes` when a data point passes the reliability check. The "Stop-and-Go" technique may be applied directly to generate an error signal which replaces the standard error signal in a digital signal equalizer system and is accompanied by algorithms for joint gain control and carrier phase adjustment.
FIG. 6 is a block diagram of a digital signal error reduction apparatus of the prior art. In FIG. 6, reference numeral 1 denotes a transversal filter. Reference numeral 2 denotes an error detector. Reference numeral 100 denotes a microprocessor (CPU) or a digital signal processor (DSP) controller. The transversal filter 1 receives a digital signal and reduces signal error. The error detector 2 receives an output of the transversal filter 1 and outputs an error signal e(t) based on the blind error estimation techniques. The CPU or DSP controller 100 receives an input digital signal z(t) and the error signal e(t) and creates coefficients for the transversal filter 1 using one of a number of traditional algorithms such as the LMS (Least Mean Square), zero forcing, MSE (Mean Square Error), FFT (Fast Fourier Transform), or any other algorithm utilized by NTSC television transmission ghost canceling tuners.
Tap coefficients are typically calculated and updated in non-real time using a microprocessor (CPU) or a digital signal processor (DSP) where signal data is first gathered by the processor and then used internally for calculations. There is a problem in that blind error estimation algorithms are inaccurate and also require many more calculations, to compute acceptable coefficients, than systems using a training reference signal. This requires much more processor time and, as a result, a slow rate of coefficient calculation is experienced. Also, typical non-real time coefficient updates are slow and quickly changing signal interferences cannot be tracked.